Summary 

Traveling using transportation has become an essential part of people’s daily routine. Nowadays, having an application that can track the location and arrival time of a transposition vehicle has become a necessity for almost everyone. This is because the application provides convenience for travel, and accurate transportation reporting enables people to plan their departure time, which saves them unnecessary waiting time and significantly improves their work efficiency. However, the City College of New York (CCNY) campus lacks such an application. This means that people on campus cannot get the exact location or waiting time of shuttle buses, which in turn can make them late for class and other important activities. Therefore, this proposal explores the development of an application that can accurately calculate and display the shuttle bus’s arrival times. This software can help users plan their travel time more safely and efficiently. This article is intended for the technical department of the City College of New York and anyone who needs to use the shuttle buses. We consider how to use a more accurate GPS for positioning, how to use code to write the backend and frontend systems of the entire app, and how to design the various pages of the app to attract people to use our software. In addition, we also made a rough calculation of the basic software development costs. The annual employee salaries costs of this software are $228,000 per year, flat-rate costs are $100 and the running costs are $8819 per year.

Authors’ Note

This paper was prepared for English 21007 taught by Professor Susan Delamare.

Introduction 

With the rapid advancement of science and technology in modern society, various novel means of transportation such as cars, subways, motorcycles, and others have been devised. These means of transportation help people travel to far places though frequent delays are a common problem faced by people who rely on public transportation. This is largely due to the need for more means to check the arrival time of public vehicles. In this information age, almost everyone owns a smartphone and to make commuters’ travel more convenient, programmers have developed tools to help people check traffic information.

Our team conducted an investigation and found that there are shuttles on the campus of the City College of New York (CCNY.) The shuttle buses will run from 6:30 am – 9:15 pm, Monday through Friday and they usually do continuous loops between these shuttle buses stations: St Nicholas Ave and W 145th Street, North Academic Center at Convent Avenue, Marshak building at Convent Avenue, St Nicholas Ave and 124th-125th Street, 135th Street, and Convent Avenue. These shuttle buses usually run according to the class schedule arranged by the school. (The City College of New York, 2023). Shuttle buses will not run during holidays, canceled classes, and breaks determined by the campus. Unfortunately, there is no software available for students to view shuttle information. This often results in students missing their shuttles and arriving late to class or waiting for indefinite periods for the next shuttle bus. This is especially difficult if there is a surplus of students waiting at the shuttles’ designated stop in extremely high and low temperatures. Therefore, our team proposes to develop an app that can provide students with shuttle information, which will help them arrive on time.

Our app’s primary functionality is to acquire and utilize location information from both software users and shuttles through an advanced high-precision global position system (GPS). This GPS employs real-time dynamic positioning, which is a global satellite navigation system that provides highly accurate geographical location information. The GPS high-precision positioning principle involves using signals transmitted by satellites to determine the precise location by calculating the distance difference between the receiver and the satellite. The advantages of this GPS are manifold: 1. Reduced initialization time and expanded effective working range; 2. Continuous base stations that enable users to observe at any time, making it easy to use and improving work efficiency; 3. A complete data monitoring system that effectively eliminates system errors and cycle slips, enhancing the reliability of differential operations; 4. True single-machine operation, which eliminates the need for users to set up a reference station, thereby reducing costs; 5. A fixed and reliable data link communication method, which reduces noise interference. This technology can achieve fast response and accurate positioning.

Secondly, our software will use the previously collected real-time location information of shuttles and users to calculate the traffic conditions on the routes of the shuttles. Then the software will display the distance between the user and the shuttles and the waiting time required by the user on the screen. This makes the information users get from our software more accurate.

Finally, considering the long-term status of this software, we will have our own source code. There are a few reasons for using our own source code: 1. Over time, the internal processes of the program will change, which will affect the performance of the software. The requirements of the system are also constantly changing, and we need to make changes according to the user’s situation. 2. We can have full processing rights over the source code and have more space for personalized customization. 3. Faced with frequent demand changes and difficult problems for troubleshooting, if the source code can be provided. If the source code can be provided, we and subsequent personnel can use the source code to self-develop the software or system to better meet the needs. 4. The source code written by our group means higher cost security and no dependence on other people. 5. This allows our system to be useful in other areas as well. Therefore, software developed by using our own source code will not bear the risk of supply interruption. 

Because the software we develop is provided to the students and employees of CCNY, we will cooperate with CCNY and obtain the user and shuttle information of the college. Taking into account the development purpose of this software, we will provide it to the CCNY campus for free to help people arrange their travel plans. But considering the maintenance costs, we may charge the City College funds for subsequent software maintenance.

We would like to provide CCNY shuttle users with an application that displays reliable updates on the campus shuttle services.

Objectives

This project aims to offer a reliable app to CCNY students, professors, and staff that announces the arrival time of the college shuttles at various stops.

• Identify the current problems with the shuttle’s arrival times.

• Identifying the most optimal tracking system implementation to enhance the efficiency and reliability of the college’s shuttle services.
• Creating a shuttle app with a mobile app developer

The task schedule (Appendix A) indicates the length of required time and tasks needed to complete our project.

Preliminary literature review 

Previous research has shown that the implementation of GPS and Real-Time Passenger Information (RTPI) has proven benefits for both the operators and the users of transportation systems. According to the Federal Aviation Administration, the Global Positioning System (GPS) is based on a network of satellites that transmit radio signals from Earth’s orbit (FAA, 2022.)  The basic GPS is free to use internationally and it is operated by different government agencies in “constellations.” To achieve tracking, a GPS receiver, i.e. the object or vehicle being tracked, will receive a combination of signals from at least four satellites that calculate its precise location and time (FAA, 2022 para. #2.) These calculations can be found using the change in time (of sending and receiving a signal) and the specific frequency and wavelength of a radio wave. In addition, GPS satellites are equipped with hyper-accurate synchronized atomic clocks (FAA, 2022.)

Thanks to the global satellite and GPS systems, we can propose better ways of using it as a tool for shuttle bus tracking. One notable contribution of the benefits of GPS is noted by Brakewood and Watkins (2019).  The results of their research prove that, due to suggested behavioral changes, Real-Time Information (RTI) results in shorter wait times, increased use of transit, and faster overall travel time (Brakewood & Watkins, 2019).  The article also qualifies these claims into five “major elements” being: travel choice, mode choice, route choice, boarding stop choice, and departure time choice (Fig 1).

Figure 1

Passenger choice impacts and benefits 

Note. Reprinted from “A literature review of the passenger benefits of real-time transit information” by Brakewood C. and Watkins K., 2019, Transport Reviews.

https://doi-org.ccny-proxy1.libr.ccny.cuny.edu/10.1080/01441647.2018.1472147

Brakewood and Watkins (2019) confirm in their study that having GPS tracking as a tool for transportation is psychologically and logically optimal. They write “Key impacts on passenger behavior and perception (are) decreases in wait times, decreases in overall travel time …changes in path choice, increased use of the transit system, increases in satisfaction, … increases in perceived levels of personal security.” In addition, this research demonstrates that a tool, such as the prospective CCNY shuttle bus app, would directly increase user satisfaction as well as the perception of improved transportation to and from campus.  It strongly solidifies the great benefit GPS and RTI have on a transportation system.

Another article of previous related research was done by Velaga et al. (2013). This article discusses the importance of RTPI as opposed to just RTI. As its name suggests, RTPI is a technology in which passengers are not only consumers of the tracking information but providers of that necessary data (Velaga et al., 2013) This method provides more accurate location metrics, where sometimes standard GPS technology can be faulty or inaccurate.

Although this particular study focuses on the implementation of RTPI in nonurban areas that lack standardized map information, it proves that RTPI is useful in any network of transport including the CCNY shuttle. This article explains that RTPI functions alongside Map Matching (MM) algorithms, which analyze satellite data and the locations of user’s phones to accurately depict the vehicular route and its correct positioning, or “link.” The MM process verifies the road link using geometric, topological, probabilistic, and advanced data (Velaga et al., 2013) This means extremely accurate location can be achieved through RTPI rather than a single vehicular GPS output. This is also highly beneficial because it simplifies the processing of the tracking system; there doesn’t need to be a relative location for the vehicle to be based on and RTPI saves costs of installing and maintaining GPS, signposts, odometers or other hardware (Velaga et al.)

Though previous literature has been crucial in our goal orientation for this shuttle bus tracking app proposal, our research is necessary because there aren’t apparent researched scenarios done on a small, private field of usability. This could complicate our goal of bringing GPS and RTPI to the CCNY community as it would make it hard to understand the best methods of an app for a limited routing map and user base. We want to maximize the potential of a GPS tracking app for a shuttle bus system that has minimal routes and only a small group of users, the CCNY community, a network run by a school organization rather than a large city or a rural area as assumed in previous related articles. The goal of our research is to implement the proven techniques of both standard GPS and RTPI to create a tracking system most optimal for our campus shuttle bus.

Technical Description of Innovation

This application is intended to work for smartphone interfaces. Our innovation is software-based so the information provided is going to be presented in a wireframe form and a flowchart. The flowchart presented in Figure 2 showcases the logical side of the user’s side of the application. The homepage (Fig. 3) consists of the top center displaying the reported delays the shuttle is experiencing during the day. Below it, there are four options of shuttle services ( location and route) for users to choose from for their desired travel. On the upper left slide of the homepage, there are sidebar icons to expand its contents. Figure 4 showcases the software’s actions to adequately display users’ shuttle information in terms of locations and arrival times to its designated stops. It is the application’s actions when the user chooses one of the gray buttons seen in Figure 3.

Figure 2 Figure 3

Flowchart for the user’s end of the application Application’s homepage

Note. Flowchart showing the user actions on the app.     Note. Wireframe for homepage.

Own work.       Own work.

Figure 4

Application’s actions for locating the shuttle

Note. The flowchart showcases the app’s action when the user chooses a location and route. Own work.

Homepage

1. Sidebar

There is a sidebar icon (three lines stacked on one another) that opens up a sidebar that allows the user to either report a problem or log out. 

Report a problem

This button allows users to report an issue they experienced with the app (e.i inaccuracies or a bug).

Log out

This button will swiftly logs the user out of the application.

2. Destinations 

These four buttons allow users to look at the arrival time and location of the shuttle on the desired route. 

125th to campus

Opens up to the real-time location of the shuttle and the estimated arrival time of the shuttle from the 145th pickup spot to the campus drop-off stop.

145th to campus

Opens up to the real-time location of the shuttle and the estimated arrival time of the shuttle from the 145th pickup spot to the campus drop-off stop.

Campus to 125th

Opens up to the real-time location of the shuttle and the estimated arrival time of the shuttle from the campus pickup stop to the 125th drop-off stop.

Campus to 145th

Opens up to the real-time location of the shuttle and the estimated arrival time of the shuttle from the campus pickup stop to the 145th drop-off stop

Budget

The costs of this project are expected to reach about $236,819 annually, under the assumption of one shuttle bus vehicle. More realistically, at least two shuttle buses are required to be under our tracking, totaling around $237,689. Our costs are derived from the complexity and length of our process to maintain a tracking network amongst the CCNY shuttle buses and to design and maintain a software app that provides a user interface for that network. We have taken into account labor costs sufficient for two Software Engineers and a GPS technician as our year-round employees. We have also taken into account material costs for the GPS hardware and installation equipment. The table below demonstrates the itemized pricing for a single baseline shuttle bus.

Table 1

Budget 

Annual Employee Salaries
	Flat-Rate Costs	Running Costs
Software Engineer	–	$90,000/yr
Software Engineer	–	$90,000/yr
GPS Technician	–	$48,000/yr
Total: $228,000/yr

Materials Costs
	Flat-Rate Costs	Running Costs
GPS System (Verizon)	–	$720/yr*
GPS Installation Fee	$75*	–
Platform Fee (iOS)	–	$99/yr
Platform Fee (Android)	$25
Application Testing	–	$8,000/yr
Total: $100 + $8,819/yr
*Per Shuttle Bus

References

Brakewood, C., & Watkins, K. (2019). A literature review of the passenger benefits of real-time transit information. Transport Reviews, 39(3), 327–356.

https://doi-org.ccny-proxy1.libr.ccny.cuny.edu/10.1080/01441647.2018.1472147

Brakewood, C., & Watkins, K. (2019). A literature review of the passenger benefits of real-time transit information. Transport Reviews, 39(3), 327–356.[Image]

https://doi-org.ccny-proxy1.libr.ccny.cuny.edu/10.1080/01441647.2018.1472147

Federal Aviation Administration. (2022). Satellite navigation – GPS – How it works.  

https://www.faa.gov/about/office_org/headquarters_offices/ato/service_units/techops/navservices/gnss/gps/howitworks

The City College Of New York. (2023, September 15). Shuttle Bus Service.

https://www.ccny.cuny.edu/about/gettingthere

Velaga, N. R., Nelson, J. D., Edwards, P., Corsar, D., Sripada, S., Sharma, N., & Beecroft, M. (2013). Development of a Map-Matching Algorithm for Rural Passenger Information Systems through Mobile Phones and Crowdsourcing. Journal of Computing in Civil Engineering, 27(6), 732–742.

https://doi.org/10.1061/(asce)cp.1943-5487.0000238

Yang, Xue, Stewart, Kathleen, Tang, Luliang, Xie, Zhong, Li, Qingquan (2018). A Review of GPS

Trajectories Classification Based on Transportation Mode.                                 https://web-s-ebscohost-com.ccny-proxy1.libr.ccny.cuny.edu/ehost/pdfviewer/pdfviewer?vid=9&sid=dda1ed9e-8279-4712-a4bb-dd28ae2f6a08%40redis